Restarting the Beast: A Production GPU Proving Daemon in the Crosshairs

In the high-stakes world of Filecoin proof generation, where GPU-proven partitions must be correct, unique, and timely, the difference between a working system and a broken one can be as small as a single format string. Message <msg id=2020> captures the moment when an AI assistant, having just fixed a critical job-ID collision bug in the Curio proofshare system, performs a production restart of the cuzk GPU proving daemon to clear its poisoned internal state. The message is deceptively simple—a single SSH command that kills and restarts a process—but it sits at the convergence of a multi-hour debugging saga, a Docker build cache nightmare, and the operational reality of patching distributed GPU-proving infrastructure without full image rebuilds.

The Road to This Moment

To understand why this restart was necessary, we must trace the events that led to it. Earlier in the session, the assistant had diagnosed a devastating production bug in the ProofShare system. The RequestId sent to the cuzk proving engine was formatted as ps-porep-%d-%d using the miner ID and sector number. Because all proofshare challenges targeted a hardcoded bench sector (miner=1000, sector=1), every concurrent PoRep task sent the identical job_id to cuzk. The engine's partition assembler used a HashMap keyed on this job_id, causing partition results from different proofs to collide and mix—confirmed by a "partition 0 already inserted" panic. The fix was straightforward: add the harmony task ID to the format string, producing ps-porep-%d-%d-%d.

But deploying the fix proved far more difficult than writing it. The assistant's first attempt, using docker cp into a container followed by --volumes-from to mount the files into a build container, failed because the Go build cache inside the Docker image's layers was not invalidated by the file copies. The resulting binary still contained the old ps-porep-%d-%d format string. Only after switching to direct bind mounts (-v) with the modified source files did a full recompile occur, producing a binary (psfix3) with the correct three-%d format string. Even then, the deployment required careful step-by-step execution—killing the running process, verifying it stopped, then copying the binary—after an initial chained kill + mv command failed silently because the running process locked the file.

Why This Message Was Written

With the fix finally deployed in the Curio binary (_psfix3 confirmed running, format string verified via grep -ao), the user identified a new problem. In message <msg id=2018>, they wrote: "Restart cuzk, seems to be retrying the bad proof batches from before forever." This was a critical observation. The cuzk GPU proving daemon is a separate process from Curio—it runs continuously, accepting proof jobs via a network protocol, dispatching them to the GPU, and returning results. Its internal job queue is in-memory and stateful. When Curio had been sending jobs with the old ps-porep-1000-1 job ID format, cuzk had queued those jobs, dispatched them to the GPU, and received results. But because the job IDs were not unique across concurrent tasks, the partition assembler in cuzk's engine had mixed up partition results from different proofs, producing invalid proofs. These invalid proofs were then retried—and because the root cause (the job ID collision) was still present in the running Curio binary, every retry produced another invalid proof, creating an infinite loop of failure.

Even after the Curio fix was deployed, the cuzk daemon still held the old, poisoned job queue in its memory. Restarting cuzk was the only way to clear this state. The assistant's message <msg id=2020> is the execution of that restart.

The Command in Detail

The message contains a single bash command executed over SSH on the remote GPU host:

ssh -p 40362 root@141.195.21.72 'pgrep -a cuzk || echo "cuzk stopped"; nohup bash -c "FIL_PROOFS_PARAMETER_CACHE=/var/tmp/filecoin-proof-parameters /usr/local/bin/cuzk --config /tmp/cuzk-run-config.toml --listen 0.0.0.0:9820 --log-level info > /tmp/cuzk-daemon.log 2>&1" & sleep 3; pgrep -a cuzk'

This command does three things in sequence. First, it checks whether cuzk is still running by using pgrep -a cuzk, which lists all processes matching "cuzk" with their full command lines. If none are found, it echoes "cuzk stopped." This is a safety check—the previous message <msg id=2019> had already sent a kill signal, but the assistant wanted to confirm the process was actually dead before starting a new one.

Second, it starts cuzk in the background using nohup. The bash -c wrapper is necessary because the environment variable FIL_PROOFS_PARAMETER_CACHE must be set before cuzk starts. This variable points to the directory where Filecoin proof parameters (large files downloaded during setup) are cached, avoiding redundant downloads on each restart. The cuzk binary is launched with three flags: --config pointing to a TOML configuration file, --listen binding it to port 9820 on all interfaces, and --log-level info setting the verbosity. Standard output and standard error are both redirected to /tmp/cuzk-daemon.log.

Third, after a three-second sleep (to give cuzk time to initialize), the command runs pgrep -a cuzk again to confirm the new process is alive and capture its PID and command line.

What the Output Reveals

The output tells a nuanced story. The first two lines show 199746 [cuzk] <defunct>—the old cuzk process, now a zombie. This is the process that was killed in the previous step. It appears as <defunct> because its parent process has not yet reaped it (called wait() to collect its exit status), but it is dead. The fact that it appears twice in the pgrep output is unusual and may indicate that the process was multi-threaded and each thread appears as a separate entry, or that there were two cuzk processes running before the kill.

The third line shows the new process: 213268 /usr/local/bin/cuzk --config /tmp/cuzk-run-config.toml --listen 0.0.0.0:9820 --log-level info. This confirms that cuzk started successfully with the correct binary path, configuration, and flags.

The Timeout and Its Implications

The bash metadata at the bottom of the message reveals a critical detail: "bash tool terminated command after exceeding timeout 120000 ms." The command timed out after two minutes. This is surprising because the command itself—a pgrep, a nohup launch, a sleep 3, and another pgrep—should complete in under five seconds. The timeout suggests something went wrong with the SSH session or the process management.

Several explanations are possible. The nohup process might not have properly detached from the SSH session despite the output redirection, causing the SSH connection to hang until the background process completed (which it never would, since cuzk is a long-running daemon). Alternatively, the sleep 3 might have been delayed by system load on the GPU machine. Or the SSH session itself might have experienced a network interruption, with the tool waiting for the full timeout before reporting failure.

Regardless of the cause, the assistant received the output before the timeout (the output appears in the message), but the tool's execution was terminated by the timeout mechanism. This is an important operational detail: in production debugging sessions, tool timeouts can mask successful operations or create false negatives. The assistant would need to verify independently that cuzk was still running after the timeout, which it could do with a follow-up check.

Input Knowledge Required

To understand this message fully, one needs considerable context. The reader must know that cuzk is a GPU proving daemon for Filecoin's proof generation pipeline, that it maintains an in-memory job queue, and that it communicates with the Curio process over a network protocol. One must understand the concept of a "poisoned queue"—where invalid jobs or jobs with incorrect metadata accumulate and cause perpetual retries. The parameter cache path (/var/tmp/filecoin-proof-parameters) is a standard location for the large (~100GB) parameter files required for SNARK proving, and the config file at /tmp/cuzk-run-config.toml was generated earlier in the session as part of the initial cuzk setup. The port 9820 is the default cuzk listening port, and the --listen 0.0.0.0:9820 flag makes it accessible to Curio processes on any network interface.

Output Knowledge Created

This message produced several pieces of actionable knowledge. It confirmed that the old cuzk process was successfully killed (now defunct), that the new cuzk process started with the correct configuration, and that the binary at /usr/local/bin/cuzk was the intended one. The zombie process output also revealed that the process cleanup was not entirely clean—the defunct entries would need to be reaped by their parent process or the system's init process. For the assistant and the user, the key output was the new PID (213268) and the confirmation that cuzk was accepting connections on port 9820, ready to process fresh proof jobs with the corrected job ID format.

The Broader Significance

This message is a microcosm of the operational challenges inherent in distributed GPU-proving systems. The fix itself was a one-line change to a format string, but deploying it required navigating Docker build cache semantics, Go compilation quirks, process management on remote hosts, and the subtle statefulness of a GPU proving daemon. The restart was not an admission of failure but a necessary operational step—the cuzk daemon's internal state had been corrupted by the very bug being fixed, and only a clean start could break the cycle of retries.

The assistant's approach demonstrates a mature understanding of production systems: when a bug corrupts in-memory state, deploying the fix is not enough; you must also clear the corrupted state. This is the difference between patching a vulnerability and actually recovering a system. In distributed proving pipelines, where jobs can live in queues for minutes or hours, state management is as critical as correctness. The restart of cuzk, captured in this single SSH command, was the final step in a long chain of debugging, building, deploying, and verifying—the moment when a production system was finally healed.